Developing a Protocol for Medical Student-Organized Community-Based Hypertension Screening Programs
Bibliographic record
Abstract
Background: Hypertension screening programs have been effective in raising awareness and identifying people who are otherwise unfamiliar with their disease. We aimed to develop a resource-minimal, evidence-based protocol for a novel medical student-organized hypertension-screening program capable of community implementation. Methods: Eighty-one medical students had their blood pressure measured once using an automated machine and once using the manual auscultatory method. Bland-Altman plots compared agreement between measurement techniques. Results: No significant difference between manual and automated techniques was noted in the measurement of systolic blood pressure, but was noted for diastolic blood pressure. Conclusions: In the context of a community-based screening program, automated and manual measurements may be used interchangeably to obtain an accurate measure of systolic blood pressure. A medical student-organized community-screening program is an effective way to screen large numbers of people in a short amount of time.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.231 | 0.224 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.008 | 0.005 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.006 | 0.005 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.030 | 0.011 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".